DOI: 10.3354/cr01488
Scopus记录号: 2-s2.0-85054823312
论文题名: Time series homogenisation of large observational datasets: Impact of the number of partner series on efficiency
作者: Domonkos P. ; Coll J.
刊名: Climate Research
ISSN: 0936577X
出版年: 2017
卷: 74, 期: 1 起始页码: 31
结束页码: 42
语种: 英语
英文关键词: ACMANT
; Data quality
; Efficiency test
; Homogenisation
; Temperature
; Time series
英文摘要: Changes in climatic observations (such as station relocations and changes of instrumentation) often affect the spatial and temporal comparability of the data; therefore, an important part of improving the accuracy of observed climate variability is the time series homogenisation of the source data. In undertaking homogenisation, an essential step is the spatial comparison of the data within the same geographical region. To optimise the efficiency of homogenisation, we should know when and to what extent two series are of the same geographical origin from a climatic perspective, and how many partner series should be used. This study presents a number of novel experiments for obtaining objective answers to these questions. Monthly temperature test datasets were homogenised with ACMANT (Adapted Caussinus-Mestre Algorithm for homo - genising Networks of Temperature series) by varying the number of partner series and their spatial correlations with the candidate series. First, a homogeneous benchmark is constructed from 2 regional subsets of a simulated surface air temperature dataset from earlier work. Various kinds of inhomogeneities are then inserted into the time series, producing 5 basic types of test datasets for each geographical region. Further variation is introduced by adding additional noise to some datasets, providing more diverse spatial correlations. The results indicate that for the identifi - cation and correction of long-lasting biases in the data, the optimal number of partner series is about 30. The optimum is largely independent from the frequency and intensity of inhomogeneities and from the spatial correlation between the candidate series and its partner series. This latter finding is unexpected; hence, its possible causes and the consequences are discussed and explored more fully here. © Inter-Research 2017. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/116288
Appears in Collections: 气候减缓与适应
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Recommended Citation:
Domonkos P.,Coll J.. Time series homogenisation of large observational datasets: Impact of the number of partner series on efficiency[J]. Climate Research,2017-01-01,74(1)